We have collection of more than 1 Million open source products ranging from Enterprise product to
small libraries in all platforms. We aggregate information from all open source repositories.
Search and find the best for your needs. Check out projects section.

Tessnet2

13225

Tesseract is a C++ open source OCR engine. Tessnet2 is .NET assembly that expose very simple methods to do OCR.
Tessnet2 is multi threaded. It uses the engine the same way Tesseract.exe does. Tessdll uses another method (no thresholding).

Related Projects

GOCR is an OCR (Optical Character Recognition) program, developed under the GNU Public License. It converts scanned images of text back to text files. Joerg Schulenburg started the program, and now leads a team of developers.

Python-tesseract is an optical character recognition (OCR) tool for python. That is, it will recognize and "read" the text embedded in images. Python-tesseract is a wrapper for Google's Tesseract-OCR Engine. It is also useful as a stand-alone invocation script to tesseract, as it can read all image types supported by the Python Imaging Library, including jpeg, png, gif, bmp, tiff, and others, whereas tesseract-ocr by default only supports tiff and bmp. Additionally, if used as a script, Python-tesseract will print the recognized text instead of writing it to a file.

PyOCR is an optical character recognition (OCR) tool wrapper for python. That is, it helps using various OCR tools from a Python program.It has been tested only on GNU/Linux systems. It should also work on similar systems (*BSD, etc). It may or may not work on Windows, MacOSX, etc.

Java OCR is a suite of pure java libraries for image processing and character recognition. Small memory footprint and lack of external dependencies makes it suitable for android development. Provides modular structure for easier deployment

Conjecture is a modular, extensible, open-source C++ framework for Optical Character Recognition (OCR). It is not a single OCR, but rather an extensible collection of OCRs that can be explored, compared, extended and modified within a unified environment

ANTLR (ANother Tool for Language Recognition) is a powerful parser generator for reading, processing, executing, or translating structured text or binary files. It's widely used to build languages, tools, and frameworks. From a grammar, ANTLR generates a parser that can build and walk parse trees. Twitter search uses ANTLR for query parsing, with over 2 billion queries a day.

GATE excels at text analysis of all shapes and sizes. It provides support for diverse language processing tasks such as parsers, morphology, tagging, Information Retrieval tools, Information Extraction components for various languages, and many others. It provides support to measure, evaluate, model and persist the data structure. It could analyze text or speech. It has built-in support for machine learning and also adds support for different implementation of machine learning via plugin.

The Image Recognition and Processing Backend demonstrates how to use [AWS Step Functions] (https://aws.amazon.com/step-functions/) to orchestrate a serverless processing workflow using AWS Lambda, Amazon S3, Amazon DynamoDB and Amazon Rekognition. This workflow processes photos uploaded to Amazon S3 and extracts metadata from the image such as geolocation, size/format, time, etc. It then uses image recognition to tag objects in the photo. In parallel, it also produces a thumbnail of the photo.This repository contains sample code for all the Lambda functions depicted in the diagram below as well as an AWS CloudFormation template for creating the functions and related resources. There is also a test web app that you can run locally to interact with the backend.